hibetterheyj

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

hibetterheyj

# ref: https://stackoverflow.com/a/14241195/7961693

"""
# timestamp can be read from lidars/ folder
stamp_file_path = os.path.join(allf.lidar_dir, seq+'_stamped.npy')
lidar_stamped_dict = np.load(stamp_file_path, allow_pickle=True)
ts_np = lidar_stamped_dict.item().get('timestamp')
all_det_list = []
within_det5_list = []
within_det10_list = []

hibetterheyj

{
	// Place your snippets for python here. Each snippet is defined under a snippet name and has a prefix, body and
	// description. The prefix is what is used to trigger the snippet and the body will be expanded and inserted. Possible variables are:
	// $1, $2 for tab stops, $0 for the final cursor position, and ${1:label}, ${2:another} for placeholders. Placeholders with the
	// same ids are connected.
	// Example:
	// "Print to console": {
	// 	"prefix": "log",
	// 	"body": [
	// 		"console.log('$1');",

hibetterheyj

import os
import requests
from urllib.parse import urljoin
from bs4 import BeautifulSoup
import argparse

#%% Example
# one pdf
#   python all_pdf_dl.py -l https://memento.epfl.ch/academic-calendar/ --save-here
# many pdfs

hibetterheyj

# -*- coding: utf-8 -*-
"""
(original code running in Python2)
https://gist.github.com/aymanfarhat/6098683
@author: HYJ
"""
import random

# generate dict-based graph from txt
def load_graph():

hibetterheyj

% process path to make sure it's uniform
% ispc() 用于判定在win系统下运行，把他改成标准化的'/'
% streep()可以用于替换单个str元素或者cell array中的str
	if ispc(), base_path = strrep(base_path, '\', '/'); end
% 在行末补上一个/
	if base_path(end) ~= '/', base_path(end+1) = '/'; end